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POMDP manipulation via trajectory optimization
2015
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Efficient object manipulation based only on force feedback typically requires a plan of actively contact-seeking actions to reduce uncertainty over the true environmental model. In principle, that problem could be formulated as a full partially observable Markov decision process (POMDP) whose observations are sensed forces indicating the presence/absence of contacts with objects. Such a naive application leads to a very large POMDP with high-dimensional continuous state, action and observation
doi:10.1109/iros.2015.7353381
dblp:conf/iros/VienT15
fatcat:zktofec7gjcypd54quekwlqg5u